Acta ophthalmologica · 2019
TMIS: a new image-based software application for the measurement of tear meniscus height.
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Yang Jiarui, Zhu Xingyu, Liu Yushi, Jiang Xiaodan, Fu Jiayu, Ren Xiaotong, Li Kaixiu, Qiu Weiqiang, Li Xuemin, Yao Jun
Аннотация
PURPOSE: To present a new automated image recognition software for the measurement of tear meniscus height (TMH) and investigate its correlation and efficacy compared with an open-source software (NIH ImageJ) and manual evaluation.
METHODS: A total of 520 slit lamp photographs, among which 276 were in ×16 magnification and 244 were ×40 magnified, captured from 138 eyes of 69 healthy subjects were assessed for TMH by the new automated Tear Meniscus Identification Software (TMIS), ImageJ and human graders. Images processing of TMIS included filtration, recognition and measurement of slit lamp photographs under certain algorithm, which output two measurement patterns, TMISM ax and TMISM ean . TMH measured by ImageJ software, considered as the reference value, was conducted by a masked observer while four masked ophthalmologists performed the manual evaluation.
RESULTS: In both magnifications, TMH measured by TMISM ean showed similar values with ImageJ while manual evaluation demonstrated underestimated results, and a strong correlation was detected between TMIS and ImageJ. In ×16 magnified photographs, manually obtained TMH revealed a higher correlation with ImageJ, whereas a notably stronger correlation of TMIS with ImageJ was observed in ×40 photographs. Correspondingly, the accuracy for both TMISM ax and TMISM ean appeared to be lower than most doctors in ×16 slit lamp images, in contrast to a better precision of TMISM ean in ×40 ones.
CONCLUSION: The new software displayed high accuracy and efficacy in ×40 magnification and TMISM ean pattern, suggesting the possibility of this automated TMH measurement platform to be a valid tool in dry eye screening and follow-up practice.
METHODS: A total of 520 slit lamp photographs, among which 276 were in ×16 magnification and 244 were ×40 magnified, captured from 138 eyes of 69 healthy subjects were assessed for TMH by the new automated Tear Meniscus Identification Software (TMIS), ImageJ and human graders. Images processing of TMIS included filtration, recognition and measurement of slit lamp photographs under certain algorithm, which output two measurement patterns, TMISM ax and TMISM ean . TMH measured by ImageJ software, considered as the reference value, was conducted by a masked observer while four masked ophthalmologists performed the manual evaluation.
RESULTS: In both magnifications, TMH measured by TMISM ean showed similar values with ImageJ while manual evaluation demonstrated underestimated results, and a strong correlation was detected between TMIS and ImageJ. In ×16 magnified photographs, manually obtained TMH revealed a higher correlation with ImageJ, whereas a notably stronger correlation of TMIS with ImageJ was observed in ×40 photographs. Correspondingly, the accuracy for both TMISM ax and TMISM ean appeared to be lower than most doctors in ×16 slit lamp images, in contrast to a better precision of TMISM ean in ×40 ones.
CONCLUSION: The new software displayed high accuracy and efficacy in ×40 magnification and TMISM ean pattern, suggesting the possibility of this automated TMH measurement platform to be a valid tool in dry eye screening and follow-up practice.